{"id":"W4416332606","doi":"10.1145/3777461","title":"Blockchain Meets Securities: A Scalable Tokenization Framework","year":2025,"lang":"en","type":"article","venue":"Distributed Ledger Technologies Research and Practice","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Lexical analysis; Market liquidity; Scalability; Asset (computer security); Smart contract; Voting; Shareholder","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002203424,0.0005222806,0.0006648157,0.0006200265,0.001016865,0.002542954,0.001967382,0.001161286,0.01130661],"category_scores_gemma":[0.004341174,0.0004840592,0.0005968732,0.001037316,0.001244275,0.006275975,0.003873764,0.001714874,0.002259896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001423992,"about_ca_system_score_gemma":0.002949932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002853928,"about_ca_topic_score_gemma":0.004213745,"domain_scores_codex":[0.9983084,0.000426814,0.0001292219,0.0002744278,0.0005789885,0.0002821235],"domain_scores_gemma":[0.9981146,0.0006499359,0.0001529316,0.0006693286,0.0002067589,0.0002064619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000555306,0.0002012405,0.00116906,0.0002920575,0.00005231092,0.0005979116,0.0003440998,0.1781787,0.01147359,0.6274307,0.01217169,0.1675333],"study_design_scores_gemma":[0.0001730629,0.00009539556,0.0001244975,0.00005126464,0.00002496917,0.0001848099,0.0000675987,0.6859347,0.008179681,0.2616667,0.04346303,0.00003428389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01451387,0.0002384957,0.9714456,0.0006126478,0.00008622105,0.0002941237,0.0004107578,0.003323944,0.009074438],"genre_scores_gemma":[0.5399653,0.0006359921,0.4387079,0.0002375326,0.0001014191,0.0005770866,0.001127072,0.0004782059,0.0181695],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01130661,"threshold_uncertainty_score":0.03782439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03060166717038328,"score_gpt":0.3578237952424816,"score_spread":0.3272221280720984,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}